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.gitattributes CHANGED
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  *.zip filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - trl
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+ - ppo
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+ - transformers
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+ - reinforcement-learning
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+ ---
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+
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+ # TRL Model
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+
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+ This is a [TRL language model](https://github.com/huggingface/trl) that has been fine-tuned with reinforcement learning to
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+ guide the model outputs according to a value, function, or human feedback. The model can be used for text generation.
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+
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+ ## Usage
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+
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+ To use this model for inference, first install the TRL library:
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+
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+ ```bash
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+ python -m pip install trl
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+ ```
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+
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+ You can then generate text as follows:
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ generator = pipeline("text-generation", model="stvnl/ppo_zh_20241030_1202")
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+ outputs = generator("Hello, my llama is cute")
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+ ```
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+
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+ If you want to use the model for training or to obtain the outputs from the value head, load the model as follows:
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+
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+ ```python
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+ from transformers import AutoTokenizer
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+ from trl import AutoModelForCausalLMWithValueHead
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+
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+ tokenizer = AutoTokenizer.from_pretrained("stvnl/ppo_zh_20241030_1202")
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+ model = AutoModelForCausalLMWithValueHead.from_pretrained("stvnl/ppo_zh_20241030_1202")
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+
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+ inputs = tokenizer("Hello, my llama is cute", return_tensors="pt")
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+ outputs = model(**inputs, labels=inputs["input_ids"])
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+ ```
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+ "BloomForCausalLM"
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+ ],
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+ "hidden_size": 1024,
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+ "initializer_range": 0.02,
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+ "model_type": "bloom",
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+ "n_head": 16,
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+ "offset_alibi": 100,
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+ "skip_bias_add": true,
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+ "skip_bias_add_qkv": false,
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+ "slow_but_exact": false,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.31.0",
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+ "unk_token_id": 0,
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+ "use_cache": true,
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+ "vocab_size": 250880
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+ }
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